dst(x, location=0, scale=1, shape=0, df=Inf, log=FALSE)
dst(x, dp=, log=FALSE)
pst(x, location=0, scale=1, shape=0, df=Inf, ...)
pst(x, dp=, log=FALSE)
qst(p, location=0, scale=1, shape=0, df=Inf, tol=1e-8, ...)
qst(x, dp=, log=FALSE)
rst(n=1, location=0, scale=1, shape=0, df=Inf)
rst(x, dp=, log=FALSE)
NA
s) are allowed.pst
and qst
,
it must be of length 1.df=Inf
which corresponds
to the skew-normal distribution.dp
is specified, this overrides the
specification of the other parameters.qsn
.integrate
.dst
), probability (pst
), quantiles (qst
)
and random sample (rst
) from the skew-t distribution with given
location
, scale
, shape
and df
parameters.shape
parameter which regulates
skewness; when shape=0
, the skew-t distribution reduces to the
usual Student's t distribution. When df=Inf
, it reduces to the
skew-normal distribution. A multivariate version of the distribution exists.
See the reference below for additional information.dmst
, dsn
, psn
pdf <- dst(seq(-4,4,by=0.1), shape=3, df=5)
rnd <- rst(100, 5, 2, -5, 8)
q <- qst(c(0.25,0.5,0.75), shape=3, df=5)
pst(q, shape=3, df=5) # must give back c(0.25,0.5,0.75)
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